Senior Director, Machine Learning & AI (BPD)

Role purpose AstraZeneca's bold ambition is to be a pioneer in science, lead in our disease areas and transform patient outcomes — and by 2030, to deliver 20 new medicines and industry ‑ leading growth. Biologics are central to that ambition, and Biopharmaceutical Development (BPD) is the R&D function that turns biologic candidates into medicines. BPD develops the cell lines, bioprocesses, formulations, devices and analytical methods needed to advance biologic medicines through clinical development and approv al where they can improve the lives of patient s . As the portfolio grows in scale and complexity, BPD is increasingly adopting a Predict ‑ First CMC approach: FAIR data at source, greater use of modelling and digital twins, and AI-enabled tools that help scientists find knowledge, make decisions and create regulatory content more efficiently. The Senior Director, Machine Learning & AI leads the ML & AI team within BPD: a multidisciplinary group of specialists spanning data science, AI and data engineering, and applied machine learning research. The role is accountable for translating BPD's Predict First ambition into a coherent AI strategy and portfolio roadmap that transforms emerging technologies and promising ideas into trusted, scalable capabilities that deliver measurable scientific and business value. The Director defines the ML & AI strategy for BPD, owns delivery of the AI portfolio within the digital transformation roadmap, and serves as BPD's senior technical interface with Enterprise AI and R&D IT. The role is responsible for establishing a framework that rapidly tests and demonstrates value through proof-of-concepts ( PoCs ), accelerates adoption through iterative delivery, and enables the scaling of successful AI solutions across BPD. In addition, the Director partners closely with Robotics & Automation, Informatics, Digital Transformation, Enterprise AI, and R&D IT teams to identify opportunities where ML & AI can enhance scientific, operational, and business outcomes and to integrate AI capabilities into products, platforms, and workflows across BPD (e .g . P hysical A I) . The role provides strategic leadership on the data foundations required to enable AI at scale, including data architecture, governance, engineering, and platform capabilities, ensuring that high-quality, accessible, and trusted data can support advanced analytics, machine learning, and AI solutions across the enterprise. Success in this role requires a balance of strategic leadership and technical credibility. The Director will shape investment decisions, build organisational capability, drive adoption across BPD , influence senior stakeholders across BPD and the enterprise, and provide the technical judgement needed to guide delivery and manage risk. Key accountabilities Strategy and portfolio Define and maintain BPD’s multi-year ML&AI strategy, aligned with a Predict ‑First CMC organisation , the BPD digital transformation roadmap and AZ’s AI30 ambitions. Be accountable for the BPD AI portfolio across the four pillars: AI Foundations & Platforms, Knowledge Management, Modelling & Digital Twins, and Submission & Report Authoring. Set portfolio priorities across in-flight, self-funded and proposed initiatives, making clear, evidence-based recommendations on when to build, buy, partner, pause or stop. Technical leadership Provide senior technical oversight of model strategy, evaluation and deployment across predictive ML, mechanistic and hybrid models, protein sequence and structure models, knowledge graphs, RAG and agentic architectures. Set practical engineering standards for the team, including reproducibility, model risk management, MLOps , evaluation frameworks and human-in-the-loop approaches for GxP -adjacent use cases. Chair or lead technical review of the highest-risk or highest-value deliverables, ensuring decisions are well evidenced and risks are visible to the right governance forums. Team leadership Lead and develop a high-performing ML &AI team of data scientists and AI/data engineers, growing capability and reach through permanent hires, secondments, PDRAs and vendor partnerships. Create the operating model, ownership and delivery discipline needed for a small specialist team to have enterprise-level impact. Support AI training and culture change across BPD, helping scientists use AI well rather than simply use it more. Cross‑functional delivery Work with modelling/AI, digitalisation and robotics transformation leads to align investment, dependencies and delivery plans across AI, data and automation. Partner with R&D IT so enterprise platforms meet BPD’s scientific needs, and BPD requirements are visible in strategic platform roadmaps. Serve as BPD’s senior technical voice into Enterprise AI: adopt enterprise capability where it fits, escalate gaps, and shape shared offerings where BPD should not rebuild common capability Work closely with CMC Statistics, Informatics & Software Engineering, and Robotics & Automation Development colleagues so that ML&AI outputs sit on sound statistical, software and laboratory foundations. Build Physical AI as a